On which data evaluate an object detection model ? (similar or real life data ?)
If you want to evaluate on real thermal image dataset, you can use this one.

Thermal Image dataset

is mAP a relevant metric when I want to show result to a client ? (e.g a client doesn't understand if I tell him "my model has a mAP=0.7")


  Mean Average Precision is the relevant metric but it's more technical. You can start explaining with False Positives and False 
  Negatives in the predictions. In turn, it leads to Precision and Recall. It mostly depends upon your use case because there will always be a trade-off between them.